As already discussed, ML models can be very demanding in terms of training data, often making the task of collecting large sets of measured data infeasible. Instead of measurements, synthetic data generated by electromagnetic solvers may also be used as training data for ML propagation models. For these cases, there is an additional choice to be made, that of the solver. Some of them may be computationally more efficient than others. Moreover, it may be easier to construct the simulation environment in some solvers than others. One of the most popular ones for outdoor environments is RT [1]}, [2]}, [3]}, [4]}, [5]}, [6]}. Another deterministic method used in propagation modeling simulations is the VPE method. The method assumes a paraxial approximation with respect to the direction of propagation of the wave. Therefore, it is often used in simulating enclosed environments that have waveguiding characteristics [7]}, or terrestrial propagation scenarios [8]}.
